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An Adaptive Transfer Learning Approach for Dynamic Demand Response Potential Prediction of Load Aggregators

Accurate forecasting of aggregated demand response (DR) potential is critical for load aggregators, yet remains challenging under severe data scarcity and domain shift conditions. This paper proposes a domain-adaptive transfer learning framework based on an ensemble of Random Vector Functional-Link...

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Hoofdauteurs: Dongli Jia, Huiyu Zhan, Keyan Liu, Kunhang Xie, Bin Gou
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI AG 2026-02-01
Reeks:Energies
Onderwerpen:
demand response potential
load aggregator
transfer learning
domain adaptation
random vector functional-link network
data scarcity
Online toegang:https://www.mdpi.com/1996-1073/19/4/1083
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